The analysis of complex systems such as biological organisms is aided by the use of relational database systems for storing and retrieving large amounts of biological data. The advent of high-speed wide area networks and the Internet, together with the client/server based model of relational database management systems, is particularly well-suited for allowing researchers to access and meaningfully analyze large amounts of biological data given the appropriate hardware and software computing tools.
Computerized analysis tools are particularly useful in experimental environments involving biological response signals. By way of nonlimiting example, biological response signal data can be obtained and/or gathered using biological response signal matrices, that is, physical matrices of biological material that transmit machine-readable signals corresponding to biological content or activity at each site in the matrix. In these systems, responses to biological or environmental stimuli may be measured and analyzed in a large-scale fashion through computer-based scanning of the machine-readable signals, e.g. photons or electrical signals, into numerical matrices, and through the storage of the numerical data into relational databases.
As a further nonlimiting example, biological response signal data can be obtained and/or gathered using serial analysis of gene expression (SAGE) or other technologies for measuring gene/protein expression levels that may not use a matrix or microarray but otherwise produce measurable signals. Generally speaking, biological response signals may be measured after a perturbation of a biological sample including, for example, the exposure of a biological sample to a drug candidate, the introduction of an exogenous gene into a biological sample, the deletion of a gene from the biological sample, or changes in the culture conditions of the biological sample.
A useful outcome of the scientific experimentation being performed involves the understanding of the relationships between genes and perturbations, understanding that promotes other useful outcomes such as the invention of new drugs or other therapies. Often, relationships between perturbation and gene expression levels sheds light on known or unknown biological pathways. There is an ongoing need in the art to generate better and more useful ways for computers to assist in analyzing the large volume of biological response data that can exist for even the most simple biological organisms.